from __future__ import annotations import os from pathlib import Path from queue import SimpleQueue from threading import Thread from typing import Any import gradio as gr # type: ignore import rerun as rr from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware from gradio_rerun import Rerun # type: ignore from ocr import detect_and_log_layouts CUSTOM_PATH = "/" app = FastAPI() origins = [ "https://app.rerun.io", ] app.add_middleware( CORSMiddleware, allow_origins=origins, ) def file_ocr(log_queue: SimpleQueue[Any], file_path: str): detect_and_log_layouts(log_queue, file_path) log_queue.put("done") @rr.thread_local_stream("PaddleOCR") def log_to_rr(file_path: Path): stream = rr.binary_stream() log_queue: SimpleQueue[Any] = SimpleQueue() handle = Thread(target=file_ocr, args=[log_queue, str(file_path)]) handle.start() while True: msg = log_queue.get() if msg == "done": break msg_type = msg[0] if msg_type == "blueprint": blueprint = msg[1] rr.send_blueprint(blueprint) elif msg_type == "log": entity_path = msg[1] args = msg[2] kwargs = msg[3] if len(msg) >= 4 else {} # print(entity_path) # print(args) # print(kwargs) rr.log(entity_path, *args, **kwargs) yield stream.read() handle.join() print("done") DESCRIPTION = """ ## PaddleOCR with [Rerun](https://rerun.io/) for visualization This space demonstrates the ability to visualize and verify the document layout analysis and text detection using [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR). The [PP-Structure](https://github.com/PaddlePaddle/PaddleOCR/tree/main/ppstructure) used for this task, is an intelligent document analysis system developed by the PaddleOCR team, aims to help developers better complete tasks related to document understanding such as layout analysis and table recognition. """ with gr.Blocks() as demo: gr.Markdown(DESCRIPTION) with gr.Row(): with gr.Column(scale=1): with gr.Row(): #input_image = gr.Image(label="Input Image", image_mode="RGBA", sources="upload", type="filepath") input_file = gr.File(label="Input file (image/pdf)") with gr.Row(): button = gr.Button() with gr.Row(): gr.Examples( examples=[os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples"))], inputs=[input_file], label="Examples", cache_examples=False, examples_per_page=12, ) with gr.Column(scale=4): viewer = Rerun(streaming=True, height=900) button.click(log_to_rr, inputs=[input_file], outputs=[viewer]) app = gr.mount_gradio_app(app, demo, path=CUSTOM_PATH)